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Simone Staffa

dblp:306/5982 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Services computing and microservices · 77% Requirements engineering and software design · 12% Software maintenance and evolution · 12%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Services computing and microservices
microservice architecture
0.812024
Cromlech: Semi-Automated Monolith Decomposition Into Microservices · IEEE Trans. Serv. Comput. 2024
Services computing and microservices › microservice architecture
monolith decomposition
0.812024
Cromlech: Semi-Automated Monolith Decomposition Into Microservices · IEEE Trans. Serv. Comput. 2024
Software maintenance and evolution › refactoring
architectural refactoring
0.212024
Cromlech: Semi-Automated Monolith Decomposition Into Microservices · IEEE Trans. Serv. Comput. 2024
Requirements engineering and software design
software architecture
0.212024
Cromlech: Semi-Automated Monolith Decomposition Into Microservices · IEEE Trans. Serv. Comput. 2024

Methods — techniques the papers use, named apart from their topics

optimization · 0.8clustering · 0.8
YearPublicationVenuePosition
2024 Cromlech: Semi-Automated Monolith Decomposition Into Microservices
abstract
Microservices architectures conceive an application as a composition of loosely-coupled sub-systems that are developed, deployed, maintained, updated, and scaled independently. Compared to monoliths, microservices speed up evolution and increase flexibility. For these reasons they are becoming the reference architecture for many practitioners. A key challenge to embrace a microservices architecture is how to decompose an application into microservices: a choice that deeply affects all subsequent development phases in ways that are difficult to foresee and evaluate. Without any tool to support their reasoning, developers may erroneously evaluate the various alternatives, leading to inaccurate decomposition choices that would result in increased development, operations, and maintenance costs. This paper tackles the problem with Cromlech, a semi-automatic tool to decompose a software system into microservices. Cromlech (i) takes in input a high-level model of the system in terms of functionalities and data entities accessed by those functionalities, (ii) formulates decomposition as an optimization problem, and (iii) outputs a proposed placement of functionalities and data onto microservices, using a visual representation that helps reasoning on the resulting architecture. Cromlech evaluates design concerns, communication overheads, data management requirements, opportunities and costs of data replication. Our evaluation on a real-world industrial application shows that Cromlech consistently delivers more efficient solutions than simple heuristics and state-of-the-art approaches, and provides useful insights to developers.
Giovanni Quattrocchi, Davide Cocco, Simone Staffa, Alessandro Margara, Gianpaolo Cugola
IEEE Trans. Serv. Comput.3
2021 Pangaea: Semi-automated Monolith Decomposition into Microservices
Simone Staffa, Giovanni Quattrocchi, Alessandro Margara, Gianpaolo Cugola
ICSOC1